We describe how variable precision floating-point arithmetic can be used to compute inner products in the iterative solver GMRES. We show how the precision of the inner products carried out in the algorithm can be reduced as the iterations proceed, without affecting the convergence rate or final accuracy achieved by the iterates. Our analysis explicitly takes into account the resulting loss of orthogonality in the Arnoldi vectors. We also show how inexact matrix-vector products can be incorporated into this setting
Iterative methods are aimed at sparse linear systems that arise in many applications (e.g., PDEs, bi...
The inner product is one of the most elementary algebraic operations and the basis for a large numbe...
The increasing gap between processor performance and memory access time warrants the re-examination ...
We consider the solution of a linear system of equations using the GMRES iterative method. In [3], a...
We give a concise summary of conditions for the convergence of iterative refinement and GMRES-based ...
. The Generalized Minimal Residual Method (GMRES) is one of the significant methods for solving lin...
Abstract. Consideration of an abstract improvement algorithm leads to the following principle, which...
summary:With the emergence of mixed precision hardware, mixed precision GMRES-based iterative refine...
Motivated by the demand in machine learning, modern computer hardware is increas- ingly supporting r...
The GMRES method is a popular iterative method for the solution of large linear systems of equations...
. In [6] the Generalized Minimal Residual Method (GMRES) which constructs the Arnoldi basis and the...
We propose a general algorithm for solving a $n\times n$ nonsingular linear system $Ax = b$ based on...
International audienceIn this talk, we will consider the numerical solution of linear systems where ...
We examine the behavior of Newton's method in floating point arithmetic, allowing for extended preci...
In this paper we show how the properties of integral operators and their approximations are reflecte...
Iterative methods are aimed at sparse linear systems that arise in many applications (e.g., PDEs, bi...
The inner product is one of the most elementary algebraic operations and the basis for a large numbe...
The increasing gap between processor performance and memory access time warrants the re-examination ...
We consider the solution of a linear system of equations using the GMRES iterative method. In [3], a...
We give a concise summary of conditions for the convergence of iterative refinement and GMRES-based ...
. The Generalized Minimal Residual Method (GMRES) is one of the significant methods for solving lin...
Abstract. Consideration of an abstract improvement algorithm leads to the following principle, which...
summary:With the emergence of mixed precision hardware, mixed precision GMRES-based iterative refine...
Motivated by the demand in machine learning, modern computer hardware is increas- ingly supporting r...
The GMRES method is a popular iterative method for the solution of large linear systems of equations...
. In [6] the Generalized Minimal Residual Method (GMRES) which constructs the Arnoldi basis and the...
We propose a general algorithm for solving a $n\times n$ nonsingular linear system $Ax = b$ based on...
International audienceIn this talk, we will consider the numerical solution of linear systems where ...
We examine the behavior of Newton's method in floating point arithmetic, allowing for extended preci...
In this paper we show how the properties of integral operators and their approximations are reflecte...
Iterative methods are aimed at sparse linear systems that arise in many applications (e.g., PDEs, bi...
The inner product is one of the most elementary algebraic operations and the basis for a large numbe...
The increasing gap between processor performance and memory access time warrants the re-examination ...